Prescribed-Time Adaptive Intelligent Formation Controller for Nonlinear Multiagent Systems Based on Time-Domain Mapping

Li, Yongming; Zheng, Xingyan; Li, Kewen

doi:10.1109/tai.2023.3299439

Cited by 13 publications

(2 citation statements)

References 43 publications

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“…To suppress these adverse effects, large control gains should be set to provide sufficient control effort, which may cause oscillations [29,30]. An effective approach to overcome this problem is to design composite control schemes utilizing fuzzy logic systems [31,32], neural networks [33], reinforcement learning [34,35], and disturbance observers for disturbance compensation. Among these techniques, the extended state observer (ESO), which can estimate the lumped disturbance with little model information, has been successfully implemented in various fields.…”

Section: Introductionmentioning

confidence: 99%

Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction

Wang,

Liu,

Zhang

et al. 2024

IET Control Theory & Appl

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A dual‐motor servo mechanism is a high‐order and strong‐coupling system with unknown nonlinearity, which brings challenges to controller design to realize high‐performance tracking and synchronization. This article proposes a finite‐time command filtered control strategy to address this problem. In tracking control design, finite‐time command filters are adopted to obtain the derivatives of virtual controllers, and the “explosion of complexity” problem in backstepping is thus solved. An improved compensation system is designed to reduce filtering errors. The tracking control is developed based on the combination of finite‐time control and command filtered approach. Moreover, to deal with unknown nonlinearities and uncertainties, fast finite‐time extended state observers are developed to observe lumped disturbances for the load and motor, respectively. In synchronization control design, two opposite control actions are developed using the speed difference to force two motors to rotate synchronously. The finite‐time convergence of the tracking and synchronization errors is proved. The efficiency of the proposed control strategy is verified via experiments conducted on a dual‐motor servo turntable.

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Section: Introductionmentioning

confidence: 99%

Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction

Wang,

Liu,

Zhang

et al. 2024

IET Control Theory & Appl

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“…In recent years, there has been a surge of research interest in the domain of intelligent control, as evidenced by several notable references in the literature. [1][2][3][4][5][6] Robotics, in particular, has emerged as a pivotal area within this wave of research, spanning various applications such as ground-based specialized robots, 7 deep-sea working robots, 8 and aerospace aircraft. 9,10 Achieving fast and precise tracking performance in the presence of uncertainty is paramount in these robotic systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural network fixed‐time control for an uncertain robot with input nonlinearity

Kong,

Ouyang,

Liu

2023

Intl J Robust & Nonlinear

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The article introduces an innovative adaptive fixed‐time control strategy designed for a robot system grappling with challenges like actuator saturation and model uncertainty. Two strategies are explored: model‐based control and neural networks control. In instances of model uncertainty, neural networks are leveraged to contend with the unknown dynamics of the robot system. These networks undergo training to approximate the elusive model parameters. Through this neural network approach, we establish adaptive laws grounded in fixed‐time convergence, ensuring that system tracking errors converge to a confined range near zero within a predetermined time frame. To tackle the issue of actuator saturation, an enhanced auxiliary system is introduced. This auxiliary system is tailored to counterbalance the adverse impacts of actuator saturation, thereby augmenting the tracking performance of the robot system. The proposed control policy is rigorously analyzed using Lyapunov theory, demonstrating that the system's tracking errors converge within a fixed time frame. To validate the efficacy of the proposed methodology, both numerical simulations and practical experiments are conducted, affirming the effectiveness of the approach.

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Distributed‐filter‐based double event‐triggered formation control for stochastic nonlinear MASs under switching topologies

Peng,

Lin,

Ren

et al. 2024

Intl J Robust & Nonlinear

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This article investigates a formation control method for stochastic nonlinear multi‐agent systems (MASs) under switching topologies. To reduce the communication bandwidth occupancy, two event‐triggered mechanisms of sensor‐to‐controller and controller‐to‐actuator network channels are proposed. Taking advantage of the neural networks approximation capability, a dynamic high‐gain observer is introduced to estimate unmeasured states and tackle the non‐differentiable issue of triggered output signal. Furthermore, it should be noted that a distributed filter is employed to handle the discontinuous local reference signal resulting from switching topologies. By using discontinuous topology information, the distributed filter generates a differentiable signal to design a virtual controller. Concomitantly, a first‐order filter is implemented to avoid the problem of “explosion of complexity.” Through stability analysis, it is proven that the designed formation controller achieves boundedness in probability for all signals in the stochastic nonlinear MASs. Ultimately, a simulation is performed to confirm the viability of the control approach.

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Prescribed-Time Adaptive Intelligent Formation Controller for Nonlinear Multiagent Systems Based on Time-Domain Mapping

Cited by 13 publications

References 43 publications

Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction

Enhanced command filtered control with extended state observer for dual‐motor servo mechanisms considering backlash and friction

Adaptive neural network fixed‐time control for an uncertain robot with input nonlinearity

Distributed‐filter‐based double event‐triggered formation control for stochastic nonlinear MASs under switching topologies

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